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Ahmed Nassar

8 accepted papers

2026

MarkushGrapher-2: End-to-end Multimodal Recognition of Chemical Structures

CVPR 2026

Automatically extracting chemical structures from documents is essential for the large-scale analysis of the literature in chemistry. Automatic pipelines have been developed to recognize molecules represented either in figures or in text independently. However, methods for recognizing chemical struc

Cited by 0SourcecodeScholar
2026

Moving Beyond Sparse Grounding with Complete Screen Parsing Supervision

ICML 2026poster

Modern computer-use agents (CUA) must perceive a screen as a structured state, what elements are visible, where they are, and what text they contain, before they can reliably ground instructions and act. Yet, most available grounding datasets provide sparse supervision, with *insufficient* and *low-…

Cited by 0SourceScholar
2025

MarkushGrapher: Joint Visual and Textual Recognition of Markush Structures

CVPR 2025poster

The automated analysis of chemical literature holds promise to accelerate discovery in fields such as material science and drug development. In particular, search capabilities for chemical structures and Markush structures (chemical structure templates) within patent documents are valuable, e.g., fo…

2025

SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion

ICCV 2025poster

We introduce SmolDocling, an ultra-compact vision-language model targeting end-to-end document conversion. Our model comprehensively processes entire pages by generating DocTags, a new universal markup format that captures all page elements in their full context with location. Unlike existing approa…

2024

ESG Accountability Made Easy: DocQA at Your Service

AAAI 2024technical

We present Deep Search DocQA. This application enables information extraction from documents via a question-answering conversational assistant. The system integrates several technologies from different AI disciplines consisting of document conversion to machine-readable format (via computer vision),…

2023

MolGrapher: Graph-based Visual Recognition of Chemical Structures

ICCV 2023poster

The automatic analysis of chemical literature has immense potential to accelerate the discovery of new materials and drugs. Much of the critical information in patent documents and scientific articles is contained in figures, depicting the molecule structures. However, automatically parsing the exac…

Cited by 9PDFcodeScholar
2022

TableFormer: Table Structure Understanding With Transformers

CVPR 2022poster

Tables organize valuable content in a concise and compact representation. This content is extremely valuable for systems such as search engines, Knowledge Graph's, etc, since they enhance their predictive capabilities. Unfortunately, tables come in a large variety of shapes and sizes. Furthermore, t…

Cited by 91PDFcodeScholar
2021

Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm

IROS 2021poster

Validating the safety of autonomous systems generally requires the use of high-fidelity simulators that adequately capture the variability of real-world scenarios. However, it is generally not feasible to exhaustively search the space of simulation scenarios for failures. Adaptive stress testing (AS…

Cited by 30SourcecodeScholar